Author, as appears in the article.: Roca, C.P.; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.
Department: Enginyeria Química
URV's Author/s: PEREZ ROCA, CARLOS; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.
Keywords: gene expression profiling reproducibility Gene expression regulation
Abstract: RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression.
Thematic Areas: Enginyeria química Ingeniería química Chemical engineering
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 2045-2322
Author identifier: ; n/a; n/a; 0000-0002-2260-1224
Record's date: 2017-03-28
Journal volume: 7
Papper version: info:eu-repo/semantics/publishedVersion
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Entity: Universitat Rovira i Virgili
Journal publication year: 2017
Publication Type: Article Artículo Article
Repositori URV